Data can never be relied on 100% all the time
One key factor that a talent manager needs to keep in mind is that technology tends to outpace itself
In the organizational context, technology will blur the lines of time and space. It will potentially change everything that traditional talent management comprises. It will change the way how jobs are structured, how they are defined, how teams are put together and how work is allocated. More importantly, technology will change the demographics of the workplace as it opens up new and multiple opportunities. In terms of individual work, technology will drive productivity and generate insights for increasing efficiency. Increasing productivity and efficiency can come in one of the two ways. The first way by which an organization can increase efficiency is by making everyone more proficient in what they do. Secondly, it can provide insights about the enterprise, its products, or consumers, which are much more deep and meaningful and thereby providing them with the tools and information to improve the outcomes of their efforts. These insights can come forth in the future through a very effective and intelligent use of technology.
Big data has become a buzzword across the talent management landscape and everybody is thinking about how the large volumes of enterprise data can be mined to discern patterns that can enable their own critical decision-making. Most analytical systems existent today relies on the analysis of lag data, which is a very partial use of the value that data can provide. The same data, however, be used more effectively through better predictive models. If we look at the overall spectrum of talent management, Big Data can potentially bring positive impact in every aspect. For example, if we look at talent hiring, Big Data can predict with remarkable efficiency the profiles that are likely to be more successful in the organization. For example, a hiring manager relies on intuition and believes that a candidate who is hired from an IIM or one of the better engineering schools has a higher chance of success. But the hiring manager does not correlate this intuition with organizational data, which may be speaking a different story. There are also deeper insights that Big Data can draw such as the correlation between successes in the organization compared to a profile metric such as a candidate’s academic scores. Specifically in a large organization, Big Data can be applied in the critical area of talent deployment. For eg. an organization needs to match a requirement of placing an individual with a certain niche skill in a remote geography and that too by someone who has a desire to go would be an onerous exercise in the absence of a technology platform which runs the matching engine. The deployment otherwise will be inefficient in terms of both cost and best-fit.
Data, however enables decision-making and doesn’t make decisions for you – it is a subtle but critical difference. A talent manager always needs to keep in mind that in every decision, there is always an element of judgement and intuition – one cannot abdicate managerial decision making or hide behind data.. The responsibility still needs to rest with the manager and that accountability doesn’t shift.
Technology has the tendency to outpace itself – we tend to rest easy on early-wins and that satiates/ blunts the desire to explore the full potential of the technology.
Lastly, technology and data has a significant role to play in enabling a more ‘connected enterprise’ – it however can never be a substitute to the power of direct engagement, which at the end of the day is what shapes organization energy and culture.